The Synthesis and kinetic evaluation of lysosomotropic substrate-based probes for cathepsins B and L
Bibliographic record
Abstract
Members of the cathepsin family of cysteine proteases are gaining interest as potential imaging biomarkers and drug targets due to their multifunctional roles in a range of diseases such as cancer, asthma and arthritis. Cathepsins are also involved in important regulatory processes such as cell recycling, prohormone activation, and wound healing. Developing imaging agents with the ability to assess cathepsin activity in vivo is important for identifying the specific roles these enzymes have in disease processes. We report here novel prodrug-inspired probes for Cathepsins B and L that employ weakly basic aminoquinoline reporter groups intended to be lysosomotropic once released from the enzyme, meaning they are expected to be retained in the acidic lysosome where the majority of cysteine cathepsins are primarily active. To evaluate this approach to probe design we first synthesized a series of prodrug inspired substrates using the self-immolative linker p-aminobenzyl alcohol conjugated to four different aminoquinolines as potential reporters of enzyme activity. We then developed a convenient HPLC method to estimate kcat/KM values for well-established fluorogenic substrates to first validate our new HPLC method. Once a reliable HPLC method was developed for fluorogenic substrates consistent with data obtained on a plate reader, we then determined kcat/KM values for all novel quinoline-based probe candidates. All compounds were excellent substrates of both CTB and CTL, and three candidates were hydrolyzed with particularly efficient kcat/KM values by CTL. This suggests that efficiently hydrolyzed prodrug-inspired probes bearing aminoquinoline reporters could potentially be adapted into substrate-based PET imaging agents which offer an amplification of signal and reporter immobilization in the lysosomes of cancer cells overexpressing CTL.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".